SAP is helping create the autonomous enterprise
This is an important moment in the decades-long digital technology revolution. The pace of change, and the level of disruption impacting business, has accelerated dramatically. SAP has long led the way in integrating new technologies and today is no different. I’m going to talk about how SAP is extending its usefulness by using the power of AI to help solve core issues in the complexity of SAP tools. I’ll also consider the risks from overpromising and under delivering.?
Why does SAP need GenAI technology??
When applied to the data in SAP solutions, in addition to other unstructured data, newer large language models offer the promise of vastly improved knowledge management, automated data summarization, and an accelerated ability to embed intelligence into core business processes. For many decades SAP, in an attempt to grasp as much as possible of the relevant functional need into its digital core and building layers and layers of business process and metadata around its applications.?
One of the key factors in SAP’s continuing success as a business software platform is in its ability to manage complexity. However, this comes with cost. Maintenance of SAP solutions is often expensive: even the most experienced SAP professionals can’t cover all aspects of SAP functionalities and often ending up specializing in a very small part of the SAP functionality. Business process owners, on the customer side who may have implemented a solution quite often still can’t grasp the full process extent of the business process complexity and don’t remember why certain features were implemented. The business process itself, even within SAP solution ecosystem, consists of different steps implemented by many different people, sometimes even in different software environments with different approaches of how to log and monitor processes.??
Generative AI with its vast automation potential to read metadata, interpret metadata, read and interpret business data, summarize, understand context and learn, gives all of us the exciting potential to overcome the complexity of SAP. This will help SAP and our clients to generate new solutions to support business and will make the maintenance of SAP and other enterprise software solution more cost effective.?
Bringing AI to scale in SAP?
Integrating SAP solutions with classical and generative AI offers faster implementation and improved human + machine performance. This AI adoption combined with SAP solutions has several implications:?
Efficient and swift SAP implementation and run: Advances in AI promise radical simplification and acceleration all across the SAP software lifecycle: from process mining and recommending implementation strategies, to automating coding, to building self-healing systems and creating documentation. Imagine, for example, being able to ask a generative AI copilot to review an entire week’s error messages and tickets and then do a complete root-cause analysis. Or turn a set of functional requirements into a technical design and configuration — and even write the implementation code itself. Similarly, AI could summarize and explain the release notes for the latest SAP update in an accessible way.?
SAP has already introduced a Generative AI hub which will help to generate custom code on SAP BTP, it is a promising and understandable user interface. Integration with SAP metadata, which in combination with SAP Build creates a possibility that promises making development of new functionality even faster. An SAP based co-pilot is already launched for SuccessFactors and SAP public cloud. The offering now also uses SAP’s generative AI capabilities with Joule to generate code, create data models and test data for applications. There is a huge potential for development productivity for apps, automation, integration space and app services including customer experience and HXM space.??
The potential for greater productivity and accelerated time to market is massive. But it doesn’t end there. From creating test data to defining integration strategies to supporting code-based reviews, and even guiding and accelerating an overall SAP S/4HANA? transformation initiative, the opportunities to use generative AI to automate and augment enterprise IT are almost limitless.?
Tapping into the power of generative AI:?Both classical and new generative AI techniques are opening a wealth of new opportunities to reinvent work, automate tasks, and augment employee experiences with SAP solutions and data.??
For example, Accenture’s finance team used classical AI techniques to transform lead-to-cash with an intelligent SAP Cash Application. By passing accounts receivable data from SAP S/4HANA? to a machine learning-enabled model on SAP Business Technology Platform, the application supports the complex process of matching incoming payments against corresponding invoices and client accounts.??
The result? A huge increase in automation accuracy, with 67% of payments now either automatically matched, or else proposed and confirmed with a single click. Accenture also used classical AI to build an AI-infused solution to provide automated variance analysis and commentary during the critical finance pre-close period.??
SAP is already working many Generative applications that will extend digital core industry and functional solutions. Some of the use cases announced in Sapphire 2023 are mentioned below.?
Generative AI will possibly play a game changing role in how we generate data insights. Anyone who regularly work with business reporting knows that finding the right business report, getting the right view, selecting right filter to get answer to your business need might take you a bit of time, even if you have all the dashboards and business reports at your disposal. There often will be some view which is missing and some data piece which requires yet another iteration to collect the data insights that you need. SAP is trying to provide the answer to that with Just Ask features. A new tool SAP Datasphere Semantic Onboarding will offer new approach to building data products across SAP and other domain and a new way how to provide lightweight reporting with Just Ask feature to make access to analytics much easier. SAP also introduce vector engine capabilities which SAP Datasphere developers will enable Retrieval Augmented Generation , facilitating the combination of large language models with private business data. These applications will learn and adapt to new information thus enabling automated decision-making and empowering citizen developers.?
To speed up Generative AI adoption SAP is extending partnership with all main AI ecosystem players with emphasis on relevant, reliable and responsible Business AI . SAP has already extended it platform to strategic AI Ecosystem partners like databricks, Cohere, DataRobot, Aleph Alpha, Anthrop\C, Google, Microsoft and?IBM. Wider ecosystems play for GenAI based applications with SAP becoming a common platform across models SAP intends to interface with a host of LLM providers and AI ecosystem partners for its AI foundation platform on BTP.??
Still challenges and considerations to work through?
While technology and tools to use Generative AI are already available to a large consumer base, the adoption of the tools and further integration into various aspects of SAP software will take time, meaning we should expect some challenges and try and fails along the way. It is important to pick the right and realistic use cases and, in some cases, not put the bar for the expectations too high. Very simple cases of automation and integration can also gain massive productivity and we should choose smartly on automation examples.?
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There is still a trust issue in Generative AI. Businesses process owners, software developers and SAP consultants will have to learn the uses cases for Generative AI and how it works. The larger problem of the GenAI also is whether it will be reliable and if process owners and business can trust the explanation of its results.??
SAP users have lived in a transactional world where push of the button solves one specific problem and gives algorithmically explainable results. Generative AI on the other hand provides a conversationally descriptive problem with the several solution options, often requiring multiple iterations to provide a solution. The most likely road to providing trust in the solutions is to use a new approach where some problems will require more international approach where we learn on Generative AI logic and solution during collaboration with the SAP software. This in term will require some changes in the way typical SAP applications both for business and software developers will organize user experience, building in transparency, and progressive disclosure with the possibility to investigate solution and expandability will be a key for the user trust.?
Finally, the use of generative AI with its potential to summarize the knowledge base and provide fast answers in any domain will enable business and software professionals with new insights areas where they lack experience. This will give access to information and the knowledge in a broader and as faster way than ever before. However, we should be ready and brave enough to use this knowledge, we should be ready to learn quickly and apply the recommendations of the machine where it provides benefit. Generative AI will recommend a solution and can even do the automation, but some steps are and will remain to be taken by human, which means we should be open enough to take those steps.??
What next?
All these advances promising a wide range of business applications use cases that still about to come, promising and exciting time for those who are passionate about AI.?
Not long into the future, with Generative AI adoption at scale by SAP and its customers, their business operations will pave the way for what can be called the “autonomous enterprise ” — a?setup where numerous decisions will be leveraged by various forms of artificial intelligence. It's not long before we'll find it hard to conceive of work happening in any other manner.?
With the latest news from the SAP, we can see that SAP solutions are now integrated with Generative AI at large scale, offering a vital means to unlock a broad range of business-wide advantages.
Additional materials to learn?
For those who are interested in further exploration of General artificial intelligence use cases for SAP I recommend looking for following materials:?